---
editor_options:
  markdown:
    wrap: 72
output: pdf_document
---

# Background and Contact

This is the replication package for our book. Please cite:

> Gazmararian, Alexander F. and Tingley, Dustin. 2023. *Uncertain
> Futures: How to Unlock the Climate Impasse*. Cambridge University
> Press.

For questions, please email Alexander F. Gazmararian at
[afg2@princeton.edu](mailto:afg2@princeton.edu);
[agazmararian@gmail.com](mailto:agazmararian@gmail.com) and Dustin
Tingley at [dtingley@g.harvard.edu](mailto:dtingley@g.harvard.edu).

# Licensing and Usage Guidelines

This replication package is provided under the MIT License. This license
permits the use, modification, distribution, and private use of the
content in this package, but with no warranty as stated in the license
terms. The datasets, code, and documentation within this package are
free for academic, educational, and research purposes. We kindly request
that users cite the associated academic article when utilizing or
referencing this package in their research or publications. For any
commercial use or adaptation of the materials, please contact the author
for permission. By using or distributing this replication package, you
agree to abide by the terms and conditions of the MIT License.

# Software and Package Dependencies

Analyses were performed on a MacBook Pro (M2 chip) with 32 GB of memory
running macOS 14.1.1 and using R version 4.3.0 (2023-04-21)
[aarch64-apple-darwin20 (64-bit)].

The preamble of each script lists the package dependencies.

# Replication Instructions

1.  Load the "rep_uncertainfutures.Rproj" R Project environment. Do not
    set a working directory. The replication package is self-contained,
    using relative file paths.
2.  As described below, the R scripts are organized by survey. The book
    and Online Appendix describe which survey sample was used, which
    allows you to identify the corresponding code to replicate the
    results.

# Directory Structure and Scripts

-   **code**: This folder contains the R scripts to replicate the
    results.

-   **clawbacks**: The scripts in this folder replicate the results for
    the clawbacks experiment in both the national and local policymaker
    samples.

-   **fun**: This folder contains custom functions called in other
    scripts.

-   **govcred**: The scripts in this folder conduct the analyses about
    perceptions of government credibility.

-   **localecon**: The scripts in this folder conduct the analyses about
    perceptions of local economic opportunity.

-   **samplestats**: The scripts in this folder create summary
    statistics for the various samples.

-   **solutions**: The scripts in this folder replicate the results for
    the survey experiments exploring the solutions to build credibility.
    This includes the multi-attribute policy experiment, the delegation
    experiment, the lock-in experiment, the promises vs. laws
    experiment, the hand-tying experiment, and the second-order beliefs
    experiment.

-   **transitioncommunities**: The scripts in this folder create the map
    of energy communities.

-   **transparency**: The scripts in this folder replicate the results
    for the transparency experiment in both the national and local
    policymaker samples.

-   **workforce**: The scripts in this folder replicate the results
    pertaining to the green workforce. This includes the costly
    signaling experiment, youths career views, and the prior notice
    experiment.

-   **data**: This folder contains the processed and de-identified
    survey data.

-   **figures**: This folder contains the figures generated by the R
    scripts.

-   **tables**: This folder contains the tables generated by the R
    scripts.

-   **instruments**: This folder contains our survey instruments.

# Data Documentation

The book and Online Appendix describe the sampling procedures.

## Local Policymaker CivicPulse Sample

The dataset in this repository is the public access version. Some models include the
following covariates, which are only in the restricted access dataset:

-   `biden2020`: The proportion of the votes, by county, for Joe Biden
    in the 2020 Presidential election. Each sub-county government is
    matched to the relevant county in which it is contained.
-   `Census_area_college`: The proportion of 25-years-or-older residents
    in the given geographic unit who have completed a 4-year,
    post-secondary degree. This data is from the 2015-2019 Five Year
    Data from the US Census American Community Survey, as compiled by
    IPUMS National Historical Geographic Information System (NHGIS).
-   `Census_area_population`: The total number of residents living in
    the given geographic unit. This data is from the 2015-2019 Five Year
    Data from the US Census American Community Survey, as compiled by
    IPUMS NHGIS.
-   `Census_area_urban`: The proportion of residents in the given
    geographic unit who reside in an urban area. This data is taken from
    the 2010 Census, as compiled by IPUMS NHGIS.

There are coarser measures of these variables in the public access data:
`County_voteshare_pres_2020_bin`, `Census_area_college_bin`,
`Census_area_population_bin`, `Census_area_urban_bin`.

Please sign a Data Sharing Agreement with CivicPulse to access the
restricted data. We are happy to connect you to the CivicPulse team.
